Methods for predicting sexual maturity in male cynomolgus macaques on the basis of age, body weight, and histologic evaluation of the testes.

In pharmaceutical drug safety testing, sexual maturity is an important experimental parameter. Histologic immaturity of the tissues of the reproductive system can interfere with the interpretation of compound-related effects on the reproductive organs. In female cynomolgus macaques, determination of sexual maturity is simplified by the presence of a menstrual cycle. For male cynomolgus macaques, predicting maturity is much more difficult. In this study, we evaluated methods that would reliably predict sexual maturity in male cynomolgus macaques. The results of histologic examination of testes of control male cynomolgus macaques used for drug safety studies were examined retrospectively for evidence of sexual maturity. These data were compared with age and body weight determinations to establish statistical models for determining the probability that a male cynomolgus macaque is sexually mature. This model presents a simple prospective method of predicting sexual maturity in male cynomolgus macaques.

Relationships between organ weight and body/brain weight in the rat: what is the best analytical endpoint?

Analysis of organ weight in toxicology studies is an important endpoint for identification of potentially harmful effects of chemicals. Differences in organ weight between treatment groups are often accompanied by differences in body weight between these groups, making interpretation of organ weight differences more difficult. Using data from control rats that were part of 26 toxicity studies conducted under similar conditions, we have evaluated the relationship between organ weight and body/brain weight to determine which endpoint (organ weight, organ-to-body weight ratio, or organ-to-brain weight ratio) is likely to accurately detect target organ toxicity. This evaluation has shown that analysis of organ-to-body weight ratios is predictive for evaluating liver and thyroid gland weights, and organ-to-brain weight ratios is predictive for evaluating ovary and adrenal gland weights. Brain, heart, kidney, pituitary gland, and testes weights are not modeled well by any of the choices, and alternative analysis methods such as analysis of covariance should be utilized.